Determination of Ethanol Content in Water Kefir Using Headspace Gas Chromatography With Mass Spectrometry Detection: Matrix Extension and Methanol Characterization
Bibliographic record
Abstract
BACKGROUND: Water kefir is a fermented beverage using water, sugar, and cultured microorganism grains as the primary ingredients. Ethanol may be present at varying levels within the final product due to the fermentation process, so it is vital to have a validated method to meet regulatory, quality, and safety requirements. OBJECTIVE: This study describes using water kefir as a matrix for the evaluation of the previously validated method employing headspace gas chromatography mass spectrometry (HS-GCMS) detection for ethanol in kombucha. The study objective is to demonstrate the method originally using kombucha is also fit for the analysis of water kefir. This method will also evaluate the determination of methanol within the water kefir samples. METHOD: The matrix extension study was performed as per the AOAC INTERNATIONAL guidance documents outlined in Appendix K: Guidelines for Dietary Supplements and Botanicals using HS-GCMS for ethanol determination. Ethanol determination in each water kefir sample is quantified against an external standard calibration curve. The same instrumentation is used for methanol characterization. RESULTS: RSDr and HorRat values obtained for from the study demonstrated acceptable precision with RSDr values of 1.03 to 6.68% and HorRat values determined to be between 0.23 and 1.52 for ethanol determination within kefir samples. Similarly, acceptable values of RSDr ranging from 1.45 to 3.39% and HorRat ranging from 0.25 to 0.49 were observed with methanol determination. For methanol determination, the limit of detection (LOD) and limit of quantification (LOQ) determined for the method in this study to be 16 and 21 ppm, respectively. The methanol spike recovery study gave overall recoveries ranging from 89 to 91%, demonstrating acceptable method accuracy. CONCLUSIONS: The results of this study demonstrate the previously validated HS-GCMS method for ethanol determination in kombucha can also be used to quantify ethanol in water kefir samples. The method is also suitable for the determination of methanol within water kefir samples. HIGHLIGHTS: A straightforward method has been adapted to include the the quantification of ethanol and methanol in fermented beverages such as Water Kefir samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".